Overview

In addition to traditional topics like logistic and Poisson regression models, this book covers modern statistical analysis subjects, such as models for count variables, longitudinal data analysis, reliability analysis, and methods for dealing with missing values. It pays special attention to small samples by including exact methods for inference where possible. The authors analyze dependent outcomes from clustered and longitudinal study designs using the generalized linear mixed-effects model and weighted generalized estimating equations. They also include SAS, SPSS, and R codes for implementation of the methods discussed.

Full Product Details

9781439806241

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Reviews

The combination of more advanced and mathematical explanations, newer topics, and sample code from all major software platforms makes this book a valuable addition to the literature on categorical data analysis. -Russell L. Zaretzki, Journal of the American Statistical Association, September 2013

"""There is a lot to like about this book. The topics are well written and the issues are clearly explained. … It covers very well topics that are not traditionally discussed in CDA books and for this reason it certainly is a valuable addition to one’s bookshelf. For those who are looking for a book with a focus on applied data analysis (especially from a biostatistics perspective), this is a must-have book. For those who are interested in expanding their knowledge of recent advances in a broad range of CDA tools, [it] will serve you very well."" —Australian & New Zealand Journal of Statistics, 2015 ""… the book is well-written and for a mathematically oriented reader it should be quite easy to understand the methods introduced. Exercises, combined with practical data analyses, will certainly facilitate the adoption of the material."" —Tapio Nummi, International Statistical Review, 2014 ""The combination of more advanced and mathematical explanations, newer topics, and sample code from all major software platforms makes this book a valuable addition to the literature on categorical data analysis."" —Russell L. Zaretzki, Journal of the American Statistical Association, September 2013"

There is a lot to like about this book. The topics are well written and the issues are clearly explained. ... It covers very well topics that are not traditionally discussed in CDA books and for this reason it certainly is a valuable addition to one's bookshelf. For those who are looking for a book with a focus on applied data analysis (especially from a biostatistics perspective), this is a must-have book. For those who are interested in expanding their knowledge of recent advances in a broad range of CDA tools, [it] will serve you very well. -Australian & New Zealand Journal of Statistics, 2015 ... the book is well-written and for a mathematically oriented reader it should be quite easy to understand the methods introduced. Exercises, combined with practical data analyses, will certainly facilitate the adoption of the material. -Tapio Nummi, International Statistical Review, 2014 The combination of more advanced and mathematical explanations, newer topics, and sample code from all major software platforms makes this book a valuable addition to the literature on categorical data analysis. -Russell L. Zaretzki, Journal of the American Statistical Association, September 2013

Author Information

Wan Tang, Hua He, and Xin Tu, University of Rochester, New York, USA

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